Dissecting Data Security: 10 Elements Of a Data Security Program

Data breaches continue to plague organizations, with cyber threats such as ransomware increasing in complexity and sophistication. Remote work and cloud technologies bring an expanding attack surface and even more challenges to safeguard your data.

Fortunately, the elements of a strong data security ecosystem continue to expand. Today’s organizations have more extensive technology capabilities available to protect data assets. 

The threats to your company’s finances and reputation from data breaches require robust defenses. According to IBM’s Cost of a Data Breach Report 2023:

The global average cost of a data breach in 2023 was USD 4.45 million, a 15% increase over three years.

Enterprises that invest in proper data security can potentially protect those millions of dollars as well as preserve their reputations, boost privacy compliance, and retain their customers’ trust.

10 Key Elements Of Data Security

As you build out your data security technology stack, consider these key components of a strong data protection program:

1. Data Discovery: Find and identify your Data

Data discovery efforts should scan, identify and monitor for both structured and unstructured data across the entire enterprise, all locations, devices, systems, file types, etc. Structured data typically resides in databases and spreadsheets, while unstructured data is often created and used by the organization’s users in governed and ungoverned spaces such as their laptop hard drive, removable media or a shared network drive; documents, images, etc.  The organization needs to understand what they have and where they have it.  

Don’t skip this critical first step or you risk creating your organization’s biggest data security blind spot.

2. Data Classification: Categorize your Data

Data Classification is coming up with how to group the organization’s data into easily defined and maintained categories.  This can be unique to every organization, but should be kept simple and to a minimum number of categories that makes sense for the business; primarily for the data creators and consumers.  

Companies that bypass discovery and classification can fall victim to data sprawl. Information accumulates to the point where the organization do not know what data they have, where it is, its sensitivity, or its use.

Chris Willis, VP of Cybersecurity and Network Engineering at Sayers, says:

“You absolutely want to start with data discovery and then classify the data. You can’t go straight to data loss prevention or encryption without knowing what data you have and where it is.”

Automated solutions can tag and label data based on patterns, such as identifying data as a credit card number or a medical record number.

3. Data Protection: Protect it!

Data protection prevents unauthorized access, sharing, or loss of sensitive data, whether intentional or accidental. This is often where Data Loss Prevention (DLP) tools primarily focus.  DLP ensures compliance with regulations and protects valuable data assets.  

Data protections solutions address a variety of key areas:

• Endpoint – to monitor data contained on individual devices such as a laptop or mobile device. 
• Network – to monitor and filter data in transit between an endpoint device and network resources or even to external locations.
• Cloud – to secure data stored, shared, and accessed in cloud platforms. According to the IBM Cost of a Data Breach Report, 82% of breaches involved data stored in the cloud.
• Email – to ensure secure communication without the threat of over sharing sensitive content via an insecure medium.
• Storage – to protect data at rest.
• API – Protection for proper access management and secure integrations with others.

Data protection does not have to be one solution or vendor.  The integration of existing features within the organizations existing tools should suffice.  The ability for those tools to recognize content and tags will help tremendously.  However, some gaps and deficiencies will exist and should be augmented with specific tools to resolve.

4. Access Management: Control access to your data

Access management controls who can access sensitive data, ensuring only authorized individuals or entities have the appropriate permissions. 

This area of data protection includes managing your file permissions, setting data rights, promoting role-based access control, enabling access logging and auditing, and deploying multi-factor authentication to access critical data. 

For those organizations considering AI integration like Microsoft Copilot, performing an identity audit will be a critical step prior to allowing AI integration.

5. Data Backup and Recovery: Strengthen your business continuity

Data backup and recovery solutions can restore hardware failures, protect against ransomware attacks, restore lost files, and enable your organization to meet legal requirements for data retention.

Solution options are available to meet your scalability needs, as well as your Recovery Point Objective (RPO – age of backup data for recovery) and Recovery Time Objective (RTO – time to restore processes and data after an outage).  Organizations should also consider Immutable Storage to ensure that backups cannot be tampered with; even inadvertently.

6. Cloud Access Security Broker (CASB): Safeguard data moving to and from the cloud

Cloud access security broker (CASB) monitors, controls, and secures the use of cloud services and data. Focus areas include compliance risks, adaptive access control, and threat protection.

Enterprises also use CASB solutions to prevent shadow IT and regulate the use of certain cloud applications within the organization. 

CASB is a core functionality of Security Service Edge for Software as a Service application security. CASB serves as an intermediary between users and cloud service providers to consolidate enforcement for multiple types of security policies such as authentication, encryption, logging, and alerting.

7. Data Obfuscation: Conceal data to prevent unauthorized access

Data obfuscation conceals, alters, or scrambles data to protect sensitive information from unauthorized access. The data remains useful for authorized users while becoming unintelligible to others. 

Data obfuscation techniques include:

• Encryption. This transforms data into a scrambled format by using algorithms and a key. Authorized users need a corresponding decryption key to read the data.
• Tokenization. This technique replaces sensitive data with a unique token, which could appear to be a random alphanumeric character. The token maintains a link to the original data stored in a secure vault. 

• Masking. This replaces sensitive data with fake data. A common example is using asterisks to replace digits in a credit card number. By matching the pattern of the real data, masking protects privacy while preserving a degree of usability. 

8. Governance and Privacy Policies: Strengthen legal compliance and customer trust

Governance ensures compliance with regulations, protects sensitive data, and manages risks. Compliance requirements and regulations, such as GDPR and HIPAA, demand stringent data protection measures such as data loss protection.

Privacy policies respect individuals’ rights and expectations around how their personal information is protected.  

Assessments can help identify any gaps in your organization’s compliance and privacy policy needs. 

9. User and Entity Behavior Analytics (UEBA): Analyze patterns to identify breaches

User and Entity Behavior Analytics (UEBA) provide advanced threat detection capabilities to uncover insider threats, data exfiltration efforts, and credential abuse. 

UEBA uses machine learning algorithms to monitor and analyze patterns of user behavior within a network, then alerts when user actions deviate from their normal behavior. 

10. Physical Data Security: Don’t overlook the physical realm

Physical security prevents unauthorized access, theft, and physical damage to tangible assets such as security cameras, computers, data centers, documents, sticky notes and more. 

Solutions can even be low-tech, such as ensuring all offices and filing cabinets with potentially sensitive information are locked when not in use.  Use security cameras, modern locks and shredders.

Data Security Questions To Ask About Your Organization

Those ten key elements of data security can be part of a deeper conversation with a data security consultant, who will ask questions such as:

• What types of data do you consider most critical to your business operations? How do you currently manage and protect that data?

• What concerns do you have about insider threats? Do you have strategies in place to monitor and address those concerns?

• How confident are you in your organization’s ability to defend against increasing ransomware threats and protect your data?

• How do you see the role of data security within your broader IT strategy? What are your specific goals and desired outcomes?

• How do you contain data sprawl within your organization, especially in terms of knowing who has access to unstructured data?

• How are you protecting data within your database architecture?

• Are there any regulations that pertain to the data you possess?  Data Sovereignty, Privacy, right to be forgotten, etc…

Questions? Contact us at Sayers today to discover the right data protection solutions for your business.